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%%% ------------ 中文摘要 ---------------%%%
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\begin{cnabstract}
% 本文主要介绍和讨论了武汉大学博士毕业论文的~\LaTeX~模板.
% 指明了基本使用方法, 强调了公式排版的一些细节问题, 也指出了一些常见的排版错误.
\indent 机器人地图探索和导航是机器人自主构建未知环境地图和路径规划的核心问题之一。对提高机器人在未知环境探索地图的实时性、
精确性和鲁棒性具有重要的理论研究意义和应用价值。\\

地图构建中的探索和导航目的是实时生成机器人的导航目标控制点，使机器人在较短的时间内感知范围覆盖尽可能大的区域，如
\indent 何根据不完整的地图和坐标信息进行在线实时地更新实时机器人位姿和规划导航路径，确保整体探索路径的最优性和探索地图的完
全性、鲁棒性，是该问题面临的挑战。本文主要针对室内机器人实时地图探索和导航过程中的未知环境的地图构建、机器人定位和
机器人的路径规划问题进行研究。提出了一些新的算法和技术改进。具体的内容和创新点如下：\\

\begin{description}
\item[1.] 室内移动机器人应用程序都需要具有导航功能。尽管许多机器人可以使用地图进行导航，而有些机器人可以对所看到的东西
进行地图绘制，但很少有机器人可以自动探索其周围的环境。通常，人类必须事先提供地形图，提供障碍物的确切位置（对于公制地图）
或表示开放区域之间的连通性的图形（对于拓扑图）。结果，大多数导航机器人在未知环境中都变得毫无用处。探索有可能使机器人摆脱
这种限制。本文将探索定义为在未知环境中移动，构建可用于后续导航的地图的行为。一种好的探索策略是在合理的时间内生成完整或接近
完整的地图。本文的目标是针对通常在实际办公大楼中发现的复杂环境制定探索策略。提出了基于对边界的检测的方法。机器人可以从任
何边界看到未探索的空间，并将新的观测值添加到其地图中。从每个新的有利位置，机器人可能会看到位于其感知边缘的新边界。通过探索
每个边界或确定该边界不可访问，机器人可以构建环境中每个可到达位置的地图。基于边界的探索已在配备有声纳，红外和激光测距传感器的
PadBot室内移动机器人上实现。实验表明基于边界启发探索的SLAM方法能够高效稳定的用于探索包含椅子，书桌，书架，橱柜，大会议桌，
沙发和其他障碍物的真实办公室内环境。\\

\item[2.] 采集到的公共办公室内环境的场景十分复杂，具有高度的动态性和破坏性，通常存在密集且高流动的人群，同时环境中地图元素的人为破坏
也是不可控的。不可控的环境下的机器人导航依赖于稳定的机器人定位模块。但是在复杂的动态环境中机器人的定位实时性和精度很能保证。本
文对动态环境下采集的二维的激光地图特征进行了特征提取和相关性分析，并设计了基于启发式的蒙特卡洛的实时全局匹配和滑动窗口的局部匹
配的定位改进算法。从而构建出准确度高的环境占据栅格地图和特征线段整体轮廓图。显著提高了动态环境下机器人定位的实时性和鲁棒性。\\

\item[3.] 传统的机器人导航系统缺乏对动态环境因素的考虑，大部分机器人的导航系统对动态的环境缺乏实时的判断和作出决策的能力。与人类自身
的导航要求相差较远。针对目前导航规划算法在实际应用场景存在的问题，本文利用基于启发函数的路径规划算法的改进算法，用于机器人导航
过程中的全局路径规划和实时局部路径规划，实验表明该改进算法提升了机器人在动态复杂环境中决策的实时性和路径的平滑性。\\
\end{description}

\indent 总之，本文针对室内移动机器人导航技术应用在复杂办公场景中存在的不足和问题，分别在未知环境地图探索、机器人实时定位和路径规划三个
方面提出了新的算法和技术改进，并设计开发基于Microdoft Visual C++ 和ROS SLAM的机器人系统控制平台和机器人集成电路数据采集
和处理平台。使用自主开发的轮式机器人PadBot2.0在室内结构化环境中进行了自主的地图探索和导航试验，验证了基于未知环境地图探索和
导航算法的有效性和实时性。


\end{cnabstract}
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%%%--------- 关键词 -------- %%%
\cnkeywords{未知环境地图探索, 室内移动机器人, 启发式蒙特卡洛, 路径规划, 边界搜索}

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%%% ------------ 英文摘要 ---------------%%%
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\begin{enabstract}

\indent Robot map exploration and navigation is one of the core problems for robots to autonomously build unknown environment maps and path planning. 
It has important theoretical significance and application value for improving the real-time, accuracy and robustness of robots exploring maps in unknown environments.\\

\indent The purpose of exploration and navigation in map construction is to generate the robot's navigation target control points in real time, 
so that the robot can cover the largest area in the sensing range in a short period of time. 
How to update online in real time based on incomplete map and coordinate information. 
The pose and planning of the navigation path of the robot to ensure the optimality of the overall exploration path and the completeness and robustness of the exploration map are the challenges faced by this problem. 
This article focuses on the unknown environment of the indoor robot during real-time map exploration and navigation. 
Research on map building, robot positioning and robot path planning. 
Some new algorithms and technical improvements are proposed. The specific content and innovations are as follows:

\begin{description}

\item[1.] Indoor mobile robot applications need to have navigation capabilities. Although many robots can use maps for navigation and some robots can map what they see, few robots can automatically explore their surroundings. 
Usually Humans must provide topographic maps in advance, providing the exact locations of obstacles (for metric maps) or graphics (for topological maps) representing connectivity between open areas. 
As a result, most navigation robots have become unclear in unknown environments. 
Useless. Exploration may free the robot from this limitation. 
This article defines exploration as the act of moving in an unknown environment to build a map that can be used for subsequent navigation. 
A good exploration strategy is to generate complete or near-complete in a reasonable time. 
The goal of this article is to develop an exploration strategy for the complex environment usually found in actual office buildings. 
A method based on the detection of boundaries is proposed. The robot can see the unexplored space from any boundary and add new observations added new observations to its map. 
From each new vantage point, the robot may see it at the edge of its perception. 
By exploring each boundary or making it inaccessible, the robot can build a map of every reachable location in the environment.  
The boundary-based exploration has moved indoors in the PadBot equipped with sonar, infrared and laser ranging sensors Realized on a robot. 
Experiments show that the SLAM method based on boundary-inspired exploration can be used efficiently and stably to explore the real office environment including chairs, desks, bookshelves, cabinets, large conference tables, sofas and other obstacles.\\

\item[2.] The collected scenes of the environment in the public office are very complicated, highly dynamic and destructive, and usually there are dense and highly mobile people, and the artificial destruction of map elements in the environment is also uncontrollable. 
Robot navigation in uncontrolled environments depends on stable robot positioning modules. 
However, the real-time and accuracy of robot positioning can be guaranteed in a complex dynamic environment. 
This paper performs feature extraction and correlation analysis on the two-dimensional laser map features collected in a dynamic environment. 
An improved positioning algorithm based on heuristic Monte Carlo real-time global matching and local matching of sliding windows is designed. 
Thus, a highly accurate environment occupation raster map and overall contour map of feature line segments are constructed. 
The dynamic environment is significantly improved Real-time and robustness of robot positioning.\\

\item[3.] Traditional robot navigation systems lack the consideration of dynamic environmental factors, and most robot navigation systems lack the ability to make real-time judgments and decisions about dynamic environments. 
They are far from human navigation requirements. 
For current navigation planning algorithms. 
In the actual application scenario, this paper uses an improved algorithm of path planning algorithm based on heuristic function for global path planning and real-time local path planning in robot navigation. 
Experiments show that the improved algorithm improves the robot in dynamic and complex environments. 
Real-time decision making and smoothness of paths.\\

\end{description}

\indent In summary, this article addresses the deficiencies and problems of indoor mobile robot navigation technology in complex office scenarios, 
and proposes new algorithms and technical improvements in the areas of unknown environment map exploration, real-time robot positioning, and path planning. 
Microdoft Visual C ++ and ROS SLAM robot system control platform and robot integrated circuit data acquisition and processing platform. 
Using self-developed wheeled robot PadBot2.0 to conduct autonomous map exploration and navigation experiments in an indoor structured environment. 
Effectiveness and real-time performance of unknown environment map exploration and navigation algorithms.

\end{enabstract}
\vspace{1em}\par\vfill

%%%------ 英文关键词 ------- %%%
\enkeywords{Unknown environment map exploration, Indoor mobile robot, Heuristic Monte Carlo, Path planning, Boundary search}


